Embodiments of the disclosure relate to a device and method to extract unique elements from a sorted list.
The ability to extract unique elements from a sorted list is relevant in many industries. For example, in the image processing industry it is beneficial to determine similarities between images, calculate optical flow, and to determine if an object is present in different frames of an image. To accomplish these goals, numerical values are assigned to sections of an image, the sections being single pixels or groups of pixels. To determine similarities between images or whether an object is present in different frames, the sorted, numerical values of each image are compared to each other. The unique numerical values are of significance because they indicate if a unique feature is present in both images. To calculate optical flow, the position of the unique feature is determined in each image, and the velocity of the feature can be determined.
Traditional methods for extracting unique elements from a sorted list use scalar processors, which process only one data point at a time. Scalar processors are inefficient, and thus there exists a need for a more efficient device and method to extract unique elements from a sorted list.
What is needed is a system and method for extracting unique elements from a sorted list that is more efficient that traditional systems and methods.